AIMC Topic: Ethiodized Oil

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Water-Stable Magnetic Lipiodol Micro-Droplets as a Miniaturized Robotic Tool for Drug Delivery.

Advanced materials (Deerfield Beach, Fla.) Nov 13, 2024
Magnetic microrobots, designed to navigate the complex environments of the human body, show promise for minimally invasive diagnosis and treatment. However, their clinical adoption faces hurdles such as biocompatibility, precise control, and intellig...
Mice Robotics Animals Water Gelatin Ethiodized Oil Magnetic Iron Oxide Nanoparticles Miniaturization Humans Drug Delivery Systems
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Cone-Beam CT-Guided Transarterial Tagging of Endophytic Renal Tumors with Indocyanine Green for Robot-Assisted Partial Nephrectomy.

Journal of vascular and interventional radiology : JVIR Apr 26, 2022
PURPOSE: To evaluate the safety, efficacy, and clinical impact of preoperative cone-beam computed tomography (CT)-guided selective embolization of endophytic renal tumors with the fluorescent dye indocyanine green (ICG) and ethiodized oil in patients...
Humans Robotics Robotic Surgical Procedures Cone-Beam Computed Tomography Treatment Outcome Margins of Excision Kidney Neoplasms Indocyanine Green Ethiodized Oil Nephrectomy
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Quantitative Automated Segmentation of Lipiodol Deposits on Cone-Beam CT Imaging Acquired during Transarterial Chemoembolization for Liver Tumors: A Deep Learning Approach.

Journal of vascular and interventional radiology : JVIR Dec 16, 2021
PURPOSE: To show that a deep learning (DL)-based, automated model for Lipiodol (Guerbet Pharmaceuticals, Paris, France) segmentation on cone-beam computed tomography (CT) after conventional transarterial chemoembolization performs closer to the "grou...
Ethiodized Oil Chemoembolization, Therapeutic Deep Learning Liver Neoplasms Carcinoma, Hepatocellular Cone-Beam Computed Tomography Humans
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Predicting Treatment Response to Intra-arterial Therapies for Hepatocellular Carcinoma with the Use of Supervised Machine Learning-An Artificial Intelligence Concept.

Journal of vascular and interventional radiology : JVIR Mar 14, 2018
PURPOSE: To use magnetic resonance (MR) imaging and clinical patient data to create an artificial intelligence (AI) framework for the prediction of therapeutic outcomes of transarterial chemoembolization by applying machine learning (ML) techniques.
Sensitivity and Specificity Ethiodized Oil Male Chemoembolization, Therapeutic Middle Aged Machine Learning Antineoplastic Agents Retrospective Studies Aged Adult Humans Female Treatment Outcome Magnetic Resonance Imaging Liver Neoplasms Neoplasm Staging Contrast Media Predictive Value of Tests Carcinoma, Hepatocellular Doxorubicin
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[New FP Therapy Was Effective for a Case of Massive Hepatocellular Carcinoma].

Gan to kagaku ryoho. Cancer & chemotherapy Nov 1, 2015
A 62 year-old woman was hospitalized with the diagnosis of pneumonia, and a huge mass was recognized in the right lobe of the liver during a CT scan. AFP and PIVKA-Ⅱ were elevated to 101.05 ng/mL and 2,177 mAU/mL. The liver function test indicated Ch...
Fluorouracil Infusions, Intra-Arterial Cisplatin Liver Neoplasms Female Carcinoma, Hepatocellular Ethiodized Oil Antineoplastic Combined Chemotherapy Protocols Middle Aged Combined Modality Therapy Humans
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